Introduction

Data-based Storytelling

Daniel Winkler

Institute for Retailing & Data Science

Nils Wlömert

Preliminaries

Welcome to Data-based Storytelling!

 

Lectures

Date Time Room Topics Slides Readings
01-09-2023 1:00pm - 6:00pm LC.2.064 Introduction Introduction Lost in Data Translation, R for Data Science
01-11-2023 1:00pm - 6:00pm LC.1.038 Modelling Data Science and the Art of Persuasion
01-16-2023 1:00pm - 6:00pm LC.2.064 Visualization/Datascience in R The Psychology behind Data Visualization Techniques
01-18-2023 1:00pm - 6:00pm LC.2.064 Review Causal Pitchfork Visualization A Crash Course in Good and Bad Controls
01-20-2023 1:00pm - 3:30pm LC.2.064 Presentations / Exam

Goals

Gain the ability to create & communicate valuable insight from data

  1. Develop a Data Science Toolbox
    • Knowledge on data analysis and presentation
    • R programming skills to help implementation
  2. Gain confidence in our analysis
    • Learn (currently) common techniques
    • Cultivate a mindset for developing skills
    • Learn about common pitfalls
  3. Work hard and have a good time
    • Be open to question everything
    • Study to understand not to repeat
    • Master marketable skills for your career

[…] associate “winning” with the effort process itself. That’s the holy grail of dopamine management for success. It won’t make you dull or unhappy; it will make everything easier and more pleasurable […].

Andrew Huberman

Lost in data Translation

Lost in data Translation

Industry

Hire as many data scientists as you can find you’ll still be lost without translators to connect analytics with real business value. […] By 2025 Chief Data Officers and their teams function as a business unit with profit-and-loss responsibilities. The unit, in partnership with business teams, is responsible for ideating new ways to use data, developing a holistic enterprise data strategy (and embedding it as part of a business strategy), and incubating new sources of revenue by monetizing data services and data sharing.

McKinsey and Company

Academia

The empirics-first approach is not antagonistic to theory but rather can serve as a stepping-stone to theory. The approach lends itself well to today’s data-rich environment, which can reveal novel research questions untethered to theory. […] we argue that [empirics first] has a natural arc that bends more easily back to real-world implications.

Golder et al. (2022)

References

Golder, Peter N., Marnik G. Dekimpe, Jake T. An, Harald J. van Heerde, Darren S. U. Kim, and Joseph W. Alba. 2022. “Learning from Data: An Empirics-First Approach to Relevant Knowledge Generation.” Journal of Marketing, September, 00222429221129200. https://doi.org/10.1177/00222429221129200.